Science China Life Sciences

MotivationGut microbiota regulates host health through complex protein-protein interactions. However, deciphering this specific interactions between microbiota and human receptors remains a significant challenge due to the lack of specialized computational tools. ResultsLeveraging the hypothesis of cell communication and relevant data, HMI-Pred initially builds an ensemble classifier to screen for potential ligand sequences within microbial genomes. It then jointly evaluates sequence semantics and molecular docking to predict potential microbe-host receptor interactions.HMI-Pred achieved robust performance with F1-scores of 0.901 for microbial ligand identification and 0.883 for interaction prediction. Application to 332,381 microbial proteins revealed distinct interaction patterns: histone deacetylases (HDACs) served as broad-spectrum targets (mean score > 0.80), while G protein-coupled receptors (GPCRs) exhibited high specificity (scores 0.42-0.61). Furthermore, literature mining validated over 47% of the functional predictions, and specific immunomodulatory interactions were confirmed in Akkermansia muciniphila.HMI-Pred provides a valuable computational tool for decoding host-microbe signaling networks and facilitating the discovery of microbiome-based therapeutic targets. AvailabilityThe source code and documentation are available at https://github.com/YangLab-BUPT/HMI-Pred. Contactlihm@bupt.edu.cn

Enhancer-regulating epigenetic modifiers play critical roles in normal physiological processes and human pathogenesis. The major enhancer regulator paralogs MLL3 and MLL4 (MLL3/4) belong to the lysine methyltransferase 2 (KMT2) family, which catalyzes the methylation of lysine 4 on histone H3 (H3K4me). MLL3/4 are required for enhancer activation and are essential for mammalian development and stem cell differentiation. Recent studies have linked MLL3/4 with different metabolic pathways in the context of stem cell self-renewal and cancer cell growth; however, the underlying mechanisms remain elusive. Here, we utilize Seahorse extracellular flux analysis, stable isotope tracing, stem cell biology techniques, and transcriptomic analysis to investigate the functional relationship of MLL3/4, cellular respiration, and stem cell differentiation. Our results indicate that the loss of MLL3/4 impairs glycolytic activity and mitochondrial respiration in murine embryonic stem cells by downregulating the rate-limiting glycolytic enzyme Hexokinase 2 (HK2) and impairing the function of the Alpha-ketoglutarate dehydrogenase (OGDH) complex. Furthermore, simultaneously overexpression of HK2 and OGDH rescues defects in both cellular respiration and differentiation caused by MLL3/4 loss. Taken together, our study reveals a novel mechanism by which epigenetic machineries such as MLL3/4 govern the differentiation of pluripotent stem cells and facilitates the understanding of disease pathogenesis driven by enhancer malfunction.

ABSTRACPorcine respiratory diseases caused by extraintestinal pathogenic Escherichia coli (ExPEC) pose a severe threat to swine production and public health; however, research on respiratory tract-isolated ExPEC remains limited. This study comprehensively analyzed the genomic characteristics and antibiotic resistance gene (ARG) transfer potential of 441 ExPEC strains isolated from porcine lungs across 21 Chinese provinces (including 53 newly isolated strains from 2022-2024 and 388 NCBI-deposited strains). Phylogenetic analysis revealed that 84% of the isolates belonged to phylogroups A, B1, and C, with ST410, ST101, and ST88 as the predominant STs. The strains exhibited extensive ARG diversity, harboring 111 distinct ARG subtypes, with sul2 (81.4%), floR (73.5%), and tet (A) (68.0%) being the most prevalent. Importantly, critical "last-resort" antibiotic resistance genes (e.g., blaNDM-1/5, the mcr family, and tet (X4)) were also detected. Notably, 77.2% of the ARGs presented horizontal transfer potential, with plasmids (especially IncF family replicons) serving as core vectors, followed by integrons and transposons. Cooccurrence network analysis identified aph (3)-Ib, aph (6)-Id, sul2, and floR as core subnetworks driving multidrug resistance dissemination. Pangenomic analysis confirmed an open genome architecture, with core genes accounting for only 6%, reflecting the strains capacity to acquire exogenous genetic material via horizontal transfer. From the One Health perspective, these transferable ARGs can spread to the environment and humans through fecal discharge and the food chain. These findings underscore the importance of monitoring and controlling ExPEC infections in swine, as such strains can as reservoirs of ARGs, pose potential risks to human health, and may even act as sources of pathogenic agents responsible for human infections. IMPORTANCEPorcine respiratory ExPEC-induced diseases threaten swine production and public health, yet respiratory tract-isolated ExPEC research remains scarce. This study comprehensively analyzed 441 porcine lung ExPEC strains across 21 Chinese provinces, uncovering their dominant phylogroups, high ARG diversity (111 subtypes) and the presence of "last-resort" antibiotic resistance genes. We identified 77.2% of ARGs with horizontal transfer potential, plasmids (especially IncF family) as core vectors, and a core ARG subnetwork driving multidrug resistance. The open pangenome (6% core genes) highlights ExPECs strong capacity to acquire exogenous genes. These findings fill the research gap of respiratory ExPEC, clarify ARG transmission mechanisms in swine ExPEC, and provide critical genomic data for One Health-based AMR surveillance and control, guiding targeted strategies to mitigate ARG spread from swine to humans and the environment.

Characterized by the earliest use of pottery, the Jomon culture was a unique Neolithic culture that spread throughout the Japanese Archipelago. Previous archaeological evidence suggests that Jomon hunter-gatherers colonized the southernmost islands, the Ryukyu Archipelago, by approximately 7,000 years before present (YBP). However, genetic characteristics of the Ryukyu Jomon population and its contribution to the modern population have not been elucidated yet. In this study, we newly sequenced 273 modern and 25 ancient (6,700-900 YBP) whole genomes collected across the Ryukyu Archipelago. Our analysis demonstrated a genetic differentiation between the Hondo (Japanese mainland) and Ryukyu Jomon, dating back to [~]6,900 YBP. After the divergence from the Hondo Jomon, the Ryukyu Jomon experienced severe bottlenecks, with an effective population size of [~]2,000. Admixture between the Ryukyu Jomon and migrants from the historic Hondo population occurred [~]1,000 YBP, which corresponds to the widespread adoption of iron tools and agriculture in the Central Ryukyus. Different demographic histories between modern Hondo and Ryukyu populations resulted in different rates of Jomon ancestry in these populations. By providing a new perspective on the peopling of the Ryukyu Archipelago, this study significantly enhances our understanding of cultural transitions in the region.

Sandy beaches are dynamic coastal interfaces shaped by strong physical forcing and intense exchange between marine and terrestrial environments, yet their microbiomes remain poorly resolved at the genomic scale. Here we present a genome-resolved survey of microbial and viral communities across sandy beaches spanning a continental-scale latitudinal gradient along the Chinese coastline. By integrating cross-shore sampling, coastal geochemistry and large-scale multi-omics, we generated 978 metagenomes, 63 viromes and 72 metatranscriptomes, reconstructing 13,337 metagenome-assembled genomes and 38,255 viral populations. Sandy beach microbiomes exhibit exceptionally high genomic novelty, with more than 90% of species-level genomes representing previously undescribed taxa, suggesting that permeable coastal sediments constitute a distinct microbial and viral reservoir. Tidal zonation emerged as a dominant ecological driver structuring microbial diversity, metabolic strategies and virus-host interactions across cross-shore gradients. Genome-resolved analyses revealed systematic metabolic shifts from oxic heterotrophy in supratidal sediments toward increasingly chemolithotrophic and autotrophic pathways toward the low-intertidal and subtidal zone. Sandy beach microbiomes further encode broad potential for hydrocarbon and plastic transformation, together with diverse biosynthetic and antibiotic resistance repertoires that may mediate microbial chemical interactions. Together, these findings identify sandy beaches as a previously under-recognized microbial-viral biome shaped by tidal forcing, providing insight into microbiome evolution and coastal ecosystem resilience under increasing anthropogenic pressure.

High and low tides occur twice a day (every [~]12.4 hours), with the largest tidal ranges during spring tides around new and full moons (every [~]14.765 days). While these lunar cycles are known to influence many animal phenotypes, particularly the reproduction of coastal animals, the genetic basis of lunar-related rhythms remains unclear. Since phenotypic variation is a valuable resource for elucidating such mechanisms, we examined geographic variation in the lunar-regulated mass spawning of the grass puffer (Takifugu alboplumbeus) along the Japanese coast. We found that western populations spawn during the first half of the spring tides, whereas eastern populations spawn during the second half. Furthermore, although spawning typically occurs a few hours before high tide, this timing is restricted to a specific time window that is earlier in the western populations than in the eastern ones. Behavioral analysis of larvae also revealed a shorter free-running circadian period ({tau}) in the western population than in the eastern ones. As differences in {tau} affect individual variation in the timing of physiological functions and behaviors, we hypothesized that differences in {tau} could account for the different time windows and consequently the observed difference in spawning days. Population genomics analysis identified proline-rich transmembrane protein 1-like (prrt1l) as a candidate gene. Expression of prrt1l was observed in the circadian pacemaker suprachiasmatic nucleus, and triple CRISPR F0 knockout of prrt1l shortened the free-running period in larvae. These findings suggest a potential mechanism underlying the geographic variation in lunar-synchronized spawning behavior. HighlightsO_LIThe geographic variation exists in the lunar-regulated spawning of the grass puffer, with differences in spawning dates and times between western and eastern Japan. C_LIO_LIThe free-running period of western populations is shorter than that of eastern populations, which is consistent with their earlier spawning timing. C_LIO_LIPopulation genomics analysis identified prrt1l as a candidate gene harboring population-specific missense mutations, the knockout of which shortens the free-running period. C_LI

The intimate cohabitation between humans and their pets facilitates bidirectional microbial exchange, yet the extent and functional consequences of this transfer within the oral niche remain underexplored. Here, we employed metagenomic sequencing to characterize the oral microbiome of dogs and their owners across distinct geographic regions in China, integrating taxonomic, gene-centric, and functional analyses using public databases (BacMet, CARD, eggNOG, KEGG) to assess microbe-host associations. We found that dog-owner pairs exhibited significantly higher gene-level similarity compared to unrelated individuals, indicating a strong cohabitation-driven microbial linkage. While no major taxonomic shifts were observed in the human oral microbiome associated with pet ownership, we identified a marked enrichment of antibiotic resistance genes (ARGs)--particularly those conferring resistance to peptides, fluoroquinolones, antiseptics, diaminopyrimidines, cephalosporins, and carbapenems--in cohabiting pairs. This enrichment, together with the identification of exclusively shared ARGs (e.g., mdtF, macB, RanA), suggests the potential for horizontal gene transfer (HGT) between pet- and human-associated microbiomes. Functional profiling further revealed greater similarity in microbial metabolic pathways between cohabiting pairs than between unrelated individuals, reinforcing the likelihood of HGT as a mechanism underlying functional convergence. Collectively, these findings reveal that cohabitation with dogs reshapes the human oral microbiome at the genetic and functional levels, with potential implications for antimicrobial resistance transmission. This study provides a foundational framework for assessing the health risks associated with pet-human microbial exchange in shared living environments.

Poplar seed fibers cause environmental and health concerns, yet their developmental mechanisms remain poorly understood. Here, we constructed a high-resolution spatiotemporal transcriptomic atlas of female poplar capsules by integrating single-nucleus and spatial transcriptomics. We delineated the developmental trajectory of seed fibers, confirming their origin from placenta cells, and identified three functionally distinct fiber cell subtypes involved in initiation, metabolic support, and elongation. Weighted gene co-expression network analysis (WGCNA) identified several hub transcription factors, including PtoMYB, PtoHDT1, PtoEIF6 and PtoPDF2, that may serve as key regulators of fiber development. Our study provides a cellular-resolution framework for understanding trichome development in woody perennials and offers candidate targets for functional characterization toward breeding low-fluff poplar cultivars. HighlightsO_LIA spatiotemporal transcriptomic atlas of poplar capsule development is constructed at single-cell resolution C_LIO_LIFiber cells originate from placenta cells and comprise three functionally distinct subtypes C_LIO_LIProvides molecular targets for breeding low-fluff poplar cultivars to mitigate environmental pollution C_LI

In a healthy host, the residential microbes help regulate the growth of pathobionts, which are common members of the human gut microbiome, preventing them from causing diseases, including infections, under certain conditions. In cases of dysbiosis, this protection may be compromised. Targeted microbiome modulation offers a promising approach to restore healthy conditions in a disrupted community and consequently prevent infections using the natural colonization resistance of the microbiome. Elucidating the interaction mechanisms between microbial species within a microbiome is crucial for understanding how a microbiome can be modulated precisely and effectively to benefit the hosts well-being. Here, we investigated the interactions between the pathobiont C. perfringens and human gut commensals on physiological and molecular levels. We found that commensal strains affect C. perfringens growth by competing for substrates such as amino acids or a carbon source other than glucose. We further observed that Bacteroidaceae strains altered the levels of C. perfringens proteins, among others, the host-directed {theta}-toxin. Our findings reinforce the notion that modulating the composition of the gut microbiome is an effective strategy to prevent infections.

Anaerobic methanotrophic (ANME) archaea are important players in the microbial methane cycle, mitigating methane emissions from anoxic environments. ANME are found ubiquitously in methane-rich sediments, where they can couple anaerobic methane oxidation (AOM) to different electron acceptors such as sulfate, metal oxides, and natural organic matter (NOM). However, we still lack understanding of the geochemical niches and preferred metabolic pathways of most ANME subclades. Here, we investigated the genomic potential and ecophysiology of ANME-2a with respect to metal-dependent AOM in brackish metal-rich coastal sediments. We assembled several high-quality ANME MAGs from subclades with high strain heterogeneity and analyzed the genomic potential for metal-AOM. Additionally, we monitored long-term enrichments with various electron acceptors from the same sediments. Ultimately, we recovered 8 novel genomes of ANME-2a that clustered with an uncharacterized genus with only 2 representatives in public databases for which we propose the name Candidatus Methanoborealis. The analysis of the MAGs showed two different clusters within this genus; one comprising of MAGs from the Baltic Sea that showed high potential for extracellular electron transfer (EET) required for metal-AOM, and another cluster form more diverse environments with less EET potential. The Baltic Sea Ca. Methanoborealis were the only canonical methanotrophs in the incubations during active methane oxidation and metal reduction. Our results contribute to the understanding of the phylogenomic and metabolic diversity in ANME subclades, which will help to further characterize novel ANME lineages from complex sediment samples.

Astrocytes play a key role in neuronal homeostasis and in various neural disorders. The generation of astrocytes from neural progenitor cells (NPCs) and its functions are under a complex control of several signaling networks and transcription factors. In this study, we demonstrate that the transcription factor, GLIS similar 3 (GLIS3), which has been implicated in several neurodegenerative diseases, is highly expressed in astrocytes, and is required for the efficient differentiation of human NPCs into astrocytes. Loss of GLIS3 function greatly impairs astrocytes differentiation, resulting in reduced expression of astrocyte markers, whereas expression of exogenous GLIS3 restores the induction of astrocyte specific genes indicating a critical role for GLIS3 in astrocyte differentiation. Integrated transcriptomic and cistromic analyses revealed that GLIS3 directly regulates the transcription of several astrocyte-associated genes, including GFAP, SLC1A2, NFIA, and ATF3, in coordination with lineage-determining factors, such as STAT3, NFIA, and SOX9. We hypothesize that GLIS3 dysfunction disrupts this transcriptional network thereby contributing to astrocyte-associated neurological disorders. Identification of GLIS3 as a key regulator of astrocyte differentiation and gene expression will advance our understanding of its role in neurodegenerative diseases and may provide a new therapeutic target.

Pigs and chickens are not only the most important livestock species for global food production but also serve as key model organisms in various research disciplines. The pig is widely used in translational research due to its anatomical and physiological similarity to humans, providing valuable insights into immunology, metabolism, and disease mechanisms. In contrast, the chicken has become an essential model for studies related to poultry health, animal welfare, and developmental biology. Its externally developing embryo offers exceptional accessibility for experimental manipulation. Recent advances in genome editing technologies, particularly CRISPR/Cas9, have further expanded the potential of these species for functional genomic studies, although the efficient delivery of such tools remains a major challenge. By using virus-like particles (VLPs), we have been able to overcome this limitation. Here, we evaluated VLPs as delivery vehicles for genome engineering tools in pigs and chickens, two key livestock species at the human-animal interface. VLP-mediated delivery enabled efficient Cre recombination and high CRISPR/Cas9 editing rates in porcine cells, organoids, and oocytes, particularly when multiplexed. In chickens, VLPs supported robust Cre recombination and Cas9-mediated editing in cell culture, tracheal organ cultures, and in ovo. Reporter VLPs and dCas9 VLPs further demonstrated the versatility of this platform across porcine and avian systems. Together, these findings establish VLPs as an efficient and time-saving strategy for gene editing in livestock, with relevance for animal health, agricultural productivity, and translational One Health research.

Barley (Hordeum vulgare L.) is an important crop in the world and its seed dormancy is primarily controlled by a Mitogen-Activated Protein Kinase Kinase 3 (MKK3) gene. Although kinase activity of MKK3 and its roles in barley post-domestication have been widely studied, the pre-domestication evolution of MKK3 and the spread of nondormant alleles among global barley varieties remain largely unexplored. In this study, we analyzed MKK3 sequences in barley and its wild progenitor (H. spontaneum) and identified two polymorphic miniature inverted-repeat transposable elements (MITEs). Comparative analyses indicated that the insertions/excision of the MITEs predated the current estimates of barley domestication. Examination of the barley pangenomes coupled with droplet digital (dd) PCR revealed extensive copy number variation of MKK3 and suggested that transposons likely drove tandem amplification of the MKK3 gene on chromosome 5H. Additionally, approximately 1-Kb MKK3 sequences were found on chromosomes 1H and 6H. Further analysis indicated that these short MKK3 sequences were captured by a CACTA transposon that also contained fragments from four other expressed genes. The acquisition of MKK3 was estimated to be between 1.9-2.5 million years ago. Together, these findings illuminate the dynamic pre-domestication evolution of the MKK3 gene and suggest three independent origins of highly nondormant barley worldwide including a unique lineage predominant in Ethiopian germplasm. This study reveals the pivotal roles of transposons in MKK3 evolution and provide helpful information for understanding the complex history of MKK3 gene in barley and also for improving preharvest sprouting (PSH) tolerant varieties under distinct natural conditions.

Understanding the functions of maternal effect genes during oocyte growth is essential for elucidating the mechanisms of oogenesis and early embryonic development. However, conventional gene knockout and conditional knockout approaches require extensive breeding and are time-consuming. Here, we present a rapid in vitro gene functional analysis system that combines microinjection of mRNA, siRNA and plasmid DNA into mouse secondary follicles with a two-step oocyte growth culture system. Mouse secondary follicles were subjected to microinjection of mCherry mRNA and subsequently cultured for 15 days to produce fully grown oocytes. mCherry fluorescence persisted throughout the oocyte growth period but declined rapidly after fertilization. Despite minor cellular damage occasionally caused by microinjection, injected follicles developed normally and retained developmental competence. To evaluate the efficiency of gene suppression, we introduced siRNA targeting Dnmt3l, which is abundantly expressed during oocyte growth phase. Although Dnmt3l deficiency is known not to affect oocyte growth, we observed that oocyte growth was maintained normally despite a marked reduction in endogenous Dnmt3l mRNA levels in our knockdown model. These results demonstrate that this method enables efficient manipulation of gene expression specifically during oocyte growth while preserving developmental competence, providing a versatile platform for rapid functional screening of maternal effect genes in vitro.

Traumatic brain injury (TBI) is a major cause of mortality and long-term disability worldwide, giving rise to complex neurological complications that impact millions of individuals each year. Cellular stress and neuronal injury vary dramatically across cortical layers, vascular niches, and between the ipsilateral (injured) or contralateral (uninjured) hemispheres. There is a critical need for quantitative measures that capture the spatial distribution of injury-induced cellular changes, as well as the gene regulatory elements that drive them. Here, we developed OmicGlaze, an experimental and computational workflow for systematically profiling the spatial transcriptome and epigenome of mouse brains following mild traumatic brain injury. We established a spatial scoring system, and identified region-specific biological processes post injury, including changes in neuronal activities, cellular stress, immune response, and gliosis. Spatial assay for transposase-accessible chromatin with sequencing (Spatial ATAC-seq) generated the first epigenetic map of traumatic brain injury near single-cell resolution. Notably, we identified the Activator Protein-1 family transcription factor Atf3 as a key gene regulator of injury-induced cellular stress. Together, these spatial multi-omics analyses revealed gene regulatory network in TBI and provided a broadly applicable framework for dissecting cellular and molecular mechanisms underlying complex neurological disorders.

Designing microbial communities to generate target products is crucial for biotechnology, agriculture, and disease treatment. However, rationally designing such communities from large seed pools has become a major challenge, as the rapidly expanding number of complete microbial genomes greatly expands the search space and sharply increases the required screening time and computational cost. Here, we introduce eBiota, a platform for ab initio design of microbial communities from a pool of 21,514 strains to generate target products. eBiota not only identifies optimal strain combinations but also simulates community behaviors, including microbial interactions and relative abundances. eBiota integrates three modules: CoreBFS, a graph-based search algorithm that rapidly screens for bacteria with complete metabolic pathways related to the target product; ProdFBA, an extended flux balance analysis that identifies microbial consortia with maximal production efficiency; and DeepCooc, a deep learning model trained on 23,323 microbiome samples across various environments to infer co-occurrence patterns. We validated eBiotas capabilities in microbial community design and production efficiency calculation using public microbiome datasets, ranging from single strains to six-member consortia. Further in vitro experiments involving 94 strains confirmed eBiotas ability to identify species that inhibit pathogen growth and to accurately model the relative abundances within complex microbial communities. As an initial digital twin, eBiota provides a powerful platform for the rational design of functional microbial communities, offering new opportunities for metabolic engineering and synthetic biology.

ObjectiveAiming at the core problems prevalent in biomedical research, including the "translational distance", the difficulty in aligning cross-scale studies, and the lack of direct validation of single-cell systems biology models in human samples, this study aims to verify whether the results of transcriptome-wide Mendelian randomization (TWMR) based on large-scale populations are consistent with the causal inference results of deep learning combined with double machine learning (DML) using single-cell transcriptome data from human samples, to clarify whether statistical biology and systems biology can converge to the same biological truth, and provide methodological support for mechanism dissection and precision medicine research of complex diseases such as rheumatoid arthritis (RA). MethodsThis study integrated multi-omics data to conduct a two-stage causal inference and cross-scale validation analysis. In the first stage, based on the summary statistics of RA genome-wide association study (GWAS) from 456,348 individuals of European ancestry in the UK Biobank (UKB), and cis-expression quantitative trait locus (cis-eQTL) data from 31,684 individuals in the eQTLGen Consortium, a two-sample Mendelian randomization approach was adopted. Transcriptome-wide causal effect analysis was performed using the inverse-variance weighted (IVW) method, MR Egger regression, and weighted median method, and gene-level causal effect values were obtained after strict quality control and multiple testing correction. In the second stage, based on single-cell RNA sequencing (scRNA-seq) data from RA patients and healthy controls (RA group: 11 samples, 211,867 cells; Healthy control group: 38 samples, 456,631 cells), after preprocessing via the Seurat pipeline, batch effect correction, and cell type annotation, a hierarchical deep neural network was constructed to complete feature compression of high-dimensional expression data, and the DML framework was used to estimate the causal effects of genes on RA disease status. Finally, Pearson correlation analysis was performed to conduct cell type-specific cross-scale validation of gene-level causal effect values obtained by the two methods, and the validated model was used to quantify the causal effects of 16 RA-related pathways from the Reactome database. ResultsThis study confirmed that the gene causal effect values obtained from large-scale population TWMR analysis were significantly correlated with those calculated by the deep learning combined with DML model based on single-cell transcriptome data. Among them, the correlation was extremely significant (p<0.001) in core naive B cells (r=0.202, p=3.2e-05, n=414) and core naive CD4 T cells (r=0.102, p=0.037, n=412). The validated DML model successfully quantified the cell type-specific causal effect values of 16 RA-related signaling pathways. ConclusionStatistical biology and systems biology can converge to the same biological truth. The cross-scale consistency between the two can significantly shorten the "translational distance" in biomedical research, and realizes the direct validation of the single-cell systems biology causal model of human samples based on large-scale population genetic data, getting rid of the excessive dependence on animal/cell experimental models in traditional research. This research paradigm not only provides a new path for mechanism dissection and therapeutic target screening of complex diseases such as RA, but also provides a feasible solution for rare disease research to break through the limitation of GWAS sample size, and lays an important theoretical and methodological foundation for constructing standardized systems biology models of human complex diseases and promoting the development of precision medicine.

O_LIPlant growth is influenced by the composition of its associated microbiome. The inherent complexity and functional redundancy of natural plant microbiomes presents a formidable barrier to understanding the myriad biological interactions therein. Efforts have been made to develop synthetic microbial communities (SynComs) that can provide a rigorous and generalizable framework for the rational design of next-generation microbial products for sustainable agriculture. We test multiple strategies for stable, plant growth promoting SynCom design and evaluate the phenotypic and molecular impacts of a successful plant-SynCom interaction. C_LIO_LIWe designed 4 distinct, reduced-complexity variants of SynCom SRC1 and assessed their capacities for colonization, stability, and plant growth promotion. To understand the impact on plant performance of our highest performing SynCom variant, we characterized the hosts longitudinal transcriptional response to SynCom inoculation and corroborated the results with metabolomics analysis. C_LIO_LIThe top performing SynCom stably colonized sorghum roots and rhizospheres, elicited plant growth promotion, and induced dynamic spatiotemporal gene transcription in sorghum roots and shoots defined by modulation of growth-defense tradeoff machinery and enhanced flavonoid production. C_LIO_LIThe resultant reduced-complexity SynCom is a highly stable, soil-independent, plant growth promoting, and demonstrates the utility of colonization-based selection criteria, integrated with longitudinal transcriptomic and metabolomic characterization. C_LI

Salinity and sodicity stresses adversely affect rice growth and yield. To overcome yield losses, suitable tolerant rice cultivars can be developed through a marker-assisted breeding (MAB) program. In the present study, genomic regions associated with sodicity stress tolerance at the reproductive stage were identified using a high-density 50kSNP array in a recombinant inbred line (RIL) population derived from the contrasting rice genotypes CSR11 and MI48. A total of 50 QTLs were detected for various yield-related traits; further, 19 QTLs with [&ge;]15% of phenotypic variance were selected for integrated (omics) analysis. RNA sequencing of leaves and panicles at the reproductive stage under sodic stress conditions was employed to find differentially expressed genes. A total of 1368 and 1410 SNPs; 104 and 144 indels were found for MI48 and CSR11, respectively, within the QTL regions from resequencing. At chromosomes 1 and 6, colocalized QTLs (qPH1-1/qGP1-1 and qGP6-2/qSSI6-2) were discovered. Differentially expressed genes (DEGs) were mapped over the QTL regions selected, and SNP variations and indels were screened for colocalized QTLs. Potential candidate genes, namely Os-pGlcT1 (Os01g0133400), OsHKT2;1 (Os06g0701600) and OsHKT2;4 (Os06g0701700), OsANTH12 (Os06g0699800), and OsPTR2 (Os06g0706400), were identified as being responsible for glucose transport, ion homeostasis, pollen germination, and nitrogen use efficiency, respectively, under salt stress. Finally, our study provides important insights into the genes and potential mechanisms affecting grain yield under sodic stress in rice, which will contribute to the development of molecular markers for rice breeding programs.

City parks and other urban green spaces can bring significant benefits to the physical and mental health of city residents. However, there is limited knowledge about the microbial communities inhabiting these urban soils. Here, we applied long-read metagenomic sequencing to 58 urban soil samples from two major cities in China, enabling genome-resolved reconstruction of microbial diversity at unprecedented contiguity. We recovered 7,949 medium- and high-quality metagenome-assembled genomes, comprising 4,171 species-level genome bins, of which over 97% represent previously undescribed species. Long-read assemblies revealed extensive secondary metabolic capacity, including more than 30,000 biosynthetic gene clusters, which were highly contiguous compared with those from fragmented short-read assemblies. Beyond secondary metabolism, we uncovered over 2 million small protein families, including hundreds that are strongly enriched in the neighbourhood of defense systems and mobile genetic elements, highlighting their overlooked role in urban soils. These findings expand our understanding of the functional diversity of urban soil microbiomes and provide new insights with implications for urban public health.